"Common Lisp" matching MCP servers:

Automatically provides AI agents with proven instructions and past failure warnings for common tasks like deployment, auth, and payments, enabling flawless execution without manual configuration.

Provides access to personal/team knowledge repositories with tools to search, retrieve, and save information from various sources including Slack, Gmail, and document storage platforms.

Enables multiple AI agents to share, incrementally synchronize, and restore work context within a common scope using persistent tickets, immutable updates, and text artifacts.

MCP server that helps coding LLMs avoid re-solving common problems by serving verified minimal code samples and compatibility evidence, with tools to search, retrieve, and explain known solutions across languages and environments.

A simple, beginner-friendly Model Context Protocol (MCP) server written in Python. It lets any MCP-compatible AI client (like Claude Desktop) manage a to-do list on your computer through five tools: add, view, get by ID, complete, and delete.

Enables AI agents to search verified collective knowledge, request and fulfill cognition bounties, and contribute to immune defense through MCP tools.

Enables AI agents to create, search, and manage subject matter expert profiles, including private workspace organization and moderated sharing to a common library.

Enables accessing and managing personal/team internal knowledge repository with tools for semantic search, smart search, document listing, and saving information for future recall.

Enables agents to search, read, publish, and report reuse of problem-solving solutions via MCP.

Enables multiple AI agents to share persistent memory, interact through a game hall and AI lounge, and bridge messages to ChatGPT and Claude browser sessions via MCP tools.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

Enables software agents to maintain a signed, evidence-aware local ledger of claims, with policy-gated proposals, conflict queries, and constitution-pinned access through an MCP stdio server.

Provides a unified block-spindle-pscale function for reading, writing, and managing locks on JSON blocks across federated beaches, sed collectives, and bilateral grains.

Enables agents to retrieve, submit, critique, and verify structured knowledge records with provenance, uncertainty, and references over a public federated HTTP/MCP layer.

Enables AI agents to persist and retrieve structured thinking graphs using SQLite-backed memory with support for CRUD operations, graph search, and path finding.